The present application relates to the field of field service and diagnostics, and more particularly to systems and methods for remote diagnostics utilizing field data system modeling.
Dynamic mechanical systems may have numerous components that are software controlled. The components are subject to wear as the mechanical system ages and the software must be able to account for any wear that the components experience. The dynamic mechanical system may experience service events in the field, either in the form of a software fault where the software does not properly account for a particular situation, or in the form of a mechanical event in which a mechanical component operates abnormally.
During the design of the control software for the dynamic mechanical system, a mathematical model of the dynamic system may be used to emulate the mechanical system. This allows the software to be tested without actually having to install the software on the system. This allows the designer to rapidly evaluate the software and its functionality. The mathematical model is designed to accept a number of inputs including inputs such as a model mechanical fault to design the system to respond to such situations.
In some industries, such as the crane industry, the cost of an unexpected service event in the field may be substantial. In some instances, the service event may result in a complete work stoppage. It is therefore beneficial to be able to predict when a service event may occur and correct, or plan for the condition before it happens. This is normally done through routine inspections and maintenance. However, some crane components, such as a boom extension or outrigger extension, may be difficult to inspect without physically disassembling the component. For example, wear pads are disposed internal to the crane component and may not be accessible for inspection. Similarly, seals within a hydraulic cylinder and not visible with the cylinder in operation. To physically inspect these parts requires disassembly of the components which entails a stoppage of work. Disassembly can cause additional wear on components that may be avoided by adopting a maintenance program based on actual equipment use.
It would be useful to have a system for accurately predicting service events of a software controlled mechanical system. This would reduce the number of service events leading to downtime. Preventative maintenance will be able to be scheduled based on the use of the machine. Current preventative maintenance schedules are based on hours of operation and calendar days. The remote diagnostics system will be able include the amount of work, operational profile, weather, and other data to adjust the preventative maintenance schedule.